Data analysis: 2023 catchment nutrient reports
1.0 Comparison to nutrient water quality objectives
Water quality objectives (WQOs) are the nutrient concentrations we aim for to protect the health of the receiving water body, in this case an estuary or inlet. Total phosphorus and total nitrogen concentrations were compared to relevant water quality objectives. To do this, we used a rolling three-year wet month (June to October inclusive) median. Wet months were used because this is the time when most waterways are flowing and nutrient concentrations are usually highest. A combined three-year median helps reduce any interannual variability. This means that in the 2023 reports, we combined the collected data from June to October in the years 2021–23 inclusive, calculated the median, and compared it to the water quality objective. If the median was equal to, or below, the water quality objective then that site was reported as meeting the water quality objective. If the median was above the water quality objective then that site is reported as not meeting the water quality objective.
Different estuary catchments have different water quality objectives as outlined in the sections below.
The water quality objectives from the Bindjareb Djilba (Peel-Harvey estuary) Protection Plan (Department of Water and Environmental Regulation 2022) of 0.1 mg/L for total phosphorus and 1.2 mg/L for total nitrogen were used. When these water quality objectives are met, the risk of nuisance algal blooms are considered to be low.
The water quality objectives from the Leschenault Estuary water quality improvement plan (Hugues-dit-ciles et al 2012) of 0.1 mg/L for total phosphorus and 1.0 mg/L for total nitrogen were used. While the water quality improvement plan presents water quality objectives for both upland (subcatchments draining the Darling Scarp) and lowland (coastal plain rivers) sites, only those for lowland sites have been used as we are interested in protecting the health of the estuary.
The water quality objectives from the Scott River water quality improvement plan (White 2012) of 0.1 mg/L for total phosphorus and 1.0 mg/L for total nitrogen were used. While these water quality objectives were developed for a particular site – Brennans Ford, rather than the whole catchment, they were developed to protect the health of the Hardy Inlet and are therefore relevant to all sites in the Scott River catchment. There are currently no water quality objectives developed specifically for the Blackwood River catchment however, as this catchment also discharges to the Hardy Inlet, we decided to use the same water quality objectives in both the Scott and Blackwood river catchments to allow us to protect the health of the Hardy Inlet.
As there are currently no water quality objectives developed for the catchment of Oyster Harbour, the ANZECC (2000) default trigger values for lowland rivers of 0.065 mg/L for total phosphorus and 1.2 mg/L for total nitrogen were used.
The water quality objectives from the Hydrological and nutrient modelling of the Wilson Inlet catchment (Hennig et al in prep) of 0.1 mg/L for total phosphorus and 1.2 mg/L for total nitrogen were used.
As there are currently no water quality objectives developed for the catchment of Torbay Inlet, the ANZECC (2000) default trigger values for lowland rivers of 0.065 mg/L for total phosphorus and 1.2 mg/L for total nitrogen were used.
2.0 Nutrient classification
Nutrient classification categories help us compare the nutrient concentrations at different sites within and across estuary subcatchments. They provide a more nuanced view of nutrient concentrations at a site than just using the water quality objectives.
Nutrient classification categories were developed from the appropriate water quality objectives (see section 1.0) for each estuary. They were calculated as follows:
Calculation |
Category |
> 3 x WQO |
extreme |
> 2 x WQO – 3 x WQO |
very high |
> WQO – 2 x WQO |
high |
> ½ WQO – WQO |
moderate |
≤ ½ WQO |
low |
To calculate which nutrient category a site falls into, we used the rolling three-year, wet-month (June to October) median. This is the same data used when comparing a site to its water quality objective (see section 1.0). For these nutrient reports, we have only used the categories as a background to the nutrient concentration graphs to allow us to more easily compare the nutrient concentrations at different sites.
Loads were calculated for sites where there were sufficient flow and nutrient data available.
Annual loads were calculated by multiplying daily flow with daily nutrient concentrations and aggregating over the year. Daily concentration measurements are not available as samples were generally collected fortnightly, so daily concentration data needs to be estimated for those days without a sample to calculate the loads. To calculate these concentrations, the locally estimated scatterplot smoothing (LOESS) algorithm (Cleveland 1979) was used.
LOESS creates a flow-concentration curve by fitting a low-degree polynomial to a subset of the flow-concentration data to estimate the concentration for the flow at the centre point of the data subset. This is done for each flow value in the dataset. For days when nutrient data were collected, daily loads were calculated from the observed concentrations and flows. For days with no data, daily loads were calculated from the daily flow and the estimated concentration from the LOESS flow-concentration curve. The assumption of the LOESS algorithm is that there is a relationship between flow and concentration.
ANZECC & ARMCANZ, 2000, Australian and New Zealand guidelines for fresh and marine water quality, Australian and New Zealand Environment and Conservation Council & Agriculture and Resource Management Council of Australia and New Zealand.
Cleveland, WS 19798, Robust locally weighted regression and smoothing scatterplots, Journal of the American Statistical Association, Vol 74: 829–836.
Department of Water and Environmental Regulation, 2022, Bindjareb Djilba, a plan for the protection of the Peel-Harvey estuary, Department of Water and Environmental Regulation, Western Australia.
Hennig, K, Kelsey, P, Hall, J & Robb, M in prep, Hydrological and nutrient modelling of the Wilson Inlet catchment, Water Science Technical Series, Report no. 90, Aquatic Science Branch, Department of Water and Environmental Regulation, Perth, Western Australia.
Hugues-dit-Ciles, J, Kelsey, P, Marillier, B, Robb, M, Forbes, V & McKenna, M 2012, Leschenault estuary water quality improvement plan, Department of Water, Western Australia.
White, KS 2012, Hardy Inlet water quality improvement plan: Stage one – the Scott River catchment, Department of Water, Western Australia.
Data analysis: 2018-2019 catchment nutrient reports
1.0 Comparison to targets and trigger values
Water quality variables analysed were compared with a range of targets and trigger values. These were used as a point of reference against which to compare data points both within and between sites. Water quality was also classified using a rigorous statistical technique which reduces the effects of inter-annual variability and allows us to track changes in water quality over time (see section 2.0). This was used to assign a status for each site and variable. The most appropriate targets and trigger values for each estuary catchment were selected for comparison. These are outlined in the following sections.
Total nitrogen and total phosphorus data were compared with the concentration targets from the Bindjareb Djilba (Peel-Harvey estuary) Protection Plan (Department of Water and Environmental Regulation 2022) of 1.2 mg/L and 0.1 mg/L respectively. When these targets are met, the risk of nuisance algal blooms are considered to be low. These targets relate to the winter median concentration. However, for the Peel-Harvey catchment nutrient reports, the targets were used as a point of reference and to assist in comparisons between catchments, rather than as an actual target.
The Australian and New Zealand Environment and Conservation Council (ANZECC & ARMCANZ 2000) trigger values for lowland rivers in south-west Australia were used for comparison purposes for total ammonia, (measured as NH3-N + NH4+-N; 0.08 mg/L), nitrate (measured as NOx- -N; 0.15 mg/L), phosphate (measured as filterable reactive phosphorus; 0.04 mg/L) and pH. These values provide a concentration above which there may be a risk of adverse effect. For pH there is both an upper (8.0) and lower (6.5) trigger value which represent the acceptable pH range. All variables (except pH) were also classified using the Statewide River Water Quality Assessment (SWRWQA 2009) classification bands or the Water Resources Inventory 2014 salinity ranges (Department of Water 2014). See section 2.0, Variable classification for more information.
Total phosphorus and total nitrogen concentrations were compared with the Leschenault Estuary water quality improvement plan targets (Hugues-dit-Ciles et al 2012). These targets represent the allowable annual median winter concentrations in both lowland (TN 1.0 mg/L, TP 0.1 mg/L) and upland (TN 0.45 mg/L, TP 0.02 mg/L) catchments. While these targets are for the winter median concentration, the Leschenault Estuary catchment nutrient reports used these as a point of reference and to assist in comparisons between catchments rather than as a target value.
The Australian and New Zealand Environment and Conservation Council (ANZECC & ARMCANZ 2000) trigger values for lowland or upland rivers in south-west Australia were used for comparison purposes as appropriate. These trigger values are; total ammonia, (measured as NH3-N + NH4+-N; 0.08 mg/L lowland rivers and 0.06 mg/L upland rivers), nitrate (measured as NOx- -N; 0.15 mg/L lowland rivers and 0.2 mg/L upland rivers), phosphate (measured as filterable reactive phosphorus; 0.04 mg/L lowland rivers and 0.01 mg/L upland rivers) and pH. These values provide a value above which there may be a risk of adverse effect. For pH there is both an upper (8.0) and lower (6.5) trigger value which represent the acceptable pH range. All variables (except pH) were also classified using the Statewide River Water Quality Assessment (SWRWQA 2009) classification bands or the Water Resources Inventory 2014 salinity ranges (Department of Water 2014). See section 2.0, Variable classification for more information.
The Australian and New Zealand Environment and Conservation Council (ANZECC & ARMCANZ 2000) trigger values for lowland rivers in south-west Australia were used for comparison purposes for total nitrogen (1.2 mg/L), total phosphorus (0.065 mg/L) total ammonia, (measured as NH3-N + NH4+-N; 0.08 mg/L), nitrate (measured as NOx- -N; 0.15 mg/L), phosphate (measured as filterable reactive phosphorus; 0.04 mg/L) and pH. These values provide a value above which there may be a risk of adverse effect. For pH there is both an upper (8.0) and lower (6.5) trigger value which represent the acceptable pH range. All variables (except pH) were also classified using the Statewide River Water Quality Assessment (SWRWQA 2009) classification bands or the Water Resources Inventory 2014 salinity ranges (Department of Water 2014). See section 2.0, Variable classification for more information.
Total nitrogen and total phosphorus concentrations were compared with the Scott River water quality improvement plan targets (White 2012). These targets represent the historical median winter concentrations where lyngbya blooms were not observed in the upper Hardy Inlet. They were developed for use at Brennans Ford but have been used at all Scott River sites to allow for comparisons between sites. While these targets are for the winter median concentrations, the Scott River catchment nutrient reports used these as a point of reference and to assist in comparisons between catchments rather than as a target value.
The Australian and New Zealand Environment and Conservation Council (ANZECC & ARMCANZ 2000) trigger values for lowland rivers in south-west Australia were used for comparison purposes for total ammonia, (measured as NH3-N + NH4+-N; 0.08 mg/L), nitrate (measured as NOx- -N; 0.15 mg/L), phosphate (measured as filterable reactive phosphorus; 0.04 mg/L) and pH. These values provide a value above which there may be a risk of adverse effect. For pH there is both an upper (8.0) and lower (6.5) trigger value which represent the acceptable pH range. All variables (except pH) were also classified using the Statewide River Water Quality Assessment (SWRWQA 2009) classification bands or the Water Resources Inventory 2014 salinity ranges (Department of Water 2014). See section 2.0, Variable classification for more information.
The Australian and New Zealand Environment and Conservation Council (ANZECC & ARMCANZ 2000) trigger values for lowland rivers in south-west Australia were used for comparison purposes for total nitrogen (1.2 mg/L), total phosphorus (0.065 mg/L) total ammonia, (measured as NH3-N + NH4+-N; 0.08 mg/L), nitrate (measured as NOx- -N; 0.15 mg/L), phosphate (measured as filterable reactive phosphorus; 0.04 mg/L) and pH. These values provide a value above which there may be a risk of adverse effect. For pH there is both an upper (8.0) and lower (6.5) trigger value which represent the acceptable pH range. All variables (except pH) were also classified using the Statewide River Water Quality Assessment (SWRWQA 2009) classification bands or the Water Resources Inventory 2014 salinity ranges (Department of Water 2014). See section 2.0, Variable classification for more information.
The Australian and New Zealand Environment and Conservation Council (ANZECC & ARMCANZ 2000) trigger values for lowland rivers in south-west Australia were used for comparison purposes for total nitrogen (1.2 mg/L), total phosphorus (0.065 mg/L) total ammonia, (measured as NH3-N + NH4+-N; 0.08 mg/L), nitrate (measured as NOx- -N; 0.15 mg/L), phosphate (measured as filterable reactive phosphorus; 0.04 mg/L) and pH. These values provide a value above which there may be a risk of adverse effect. For pH there is both an upper (8.0) and lower (6.5) trigger value which represent the acceptable pH range. All variables (except pH) were also classified using the Statewide River Water Quality Assessment (SWRWQA 2009) classification bands or the Water Resources Inventory 2014 salinity ranges (Department of Water 2014). See section 2.0, Variable classification for more information.
2.0 Variable classification (modified from Hall 2010)
The total nitrogen, total phosphorus, dissolved organic carbon, total suspended solids and salinity concentrations at all catchment sites sampled as part of the Health Estuaries WA sampling programs were classified using the classification bands shown below. All classification bands (with the exception of salinity) are from the Statewide River Water Quality Assessment webpage (SWRWQA 2009). To classify the salinity data, the Water Resources Inventory 2014 salinity ranges (Department of Water 2014) were used.
Table 1: classification bands for total nitrogen, total phosphorus, dissolved organic carbon and total suspended solids (from SWRWQA 2009). If viewing on a mobile device, view table
here.
|
Classification
|
Total nitrogen (mg/L)
|
Total phosphorus (mg/L)
|
Dissolved organic carbon (mg/L)
|
Total suspended solids (mg/L)
|
|
very high
|
> 2
|
> 0.20
|
> 25
|
> 25
|
|
high
|
> 1.2 – 2
|
> 0.08 – 0.20
|
> 10 – 25
|
> 10 – 25
|
|
moderate
|
0.75 – 1.2
|
0.02 – 0.08
|
5 – 10
|
5 – 10
|
|
low
|
< 0.75
|
< 0.02
|
< 5
|
< 5
|
Table 2: classification bands for salinity (from Department of Water 2014). If viewing on a mobile device, view table here.
|
Classification
|
Salinity (mg/L)
|
|
saline
|
> 3,000
|
|
brackish
|
> 1,000 – 3,000
|
|
marginal
|
500 – 1,000
|
|
fresh
|
< 500
|
Depending on trends, chance sampling and sources of natural variation, the nutrient concentrations analysed from a monitored site will change. The nutrient status for a waterway is initially assigned using the median nutrient concentration for the first year of sampling. Subsequent status periods are assessed using the median and 90% confidence interval. If the median or all or part of the confidence interval remains in the earlier classification band, then there is no change in status. Status only changes once both the median and entire 90% confidence interval move to a different classification band.
Figure 1 shows how TN status at Mayfields Main Drain (in the Peel-Harvey catchment) was originally classified as high (the median was between 1.2 and 2.0 mg/L). By the 1992–94 period, the median had decreased and fell within the moderate classification band (0.75–1.2 mg/L); however, part of the 90% confidence interval was still in the high classification band and so the status remained high. In the 1994–96 period, both the median and 90% confidence interval fell below the high classification and hence the status changed to moderate. During the 1996–98 period the median once again dropped to a lower classification band (<0.75 mg/L); however, it wasn’t until the 1998–2000 period that the actual classification status changed to low.
In summary, the nutrient status for a waterway is assigned by using the median of nutrient concentration over a three-year period. The three-year period is used to reduce the influence of natural variation between years. Change in status requires the median and whole 90% confidence interval to be within the new status concentration range.
Figure 1: Total nitrogen status classification for Mayfields Main Drain (AWRC 613031)
3.0 Statistical trend testing methodology (modified from Hall 2010)
3.1 Testing for statistically significant changes
The Mann-Kendall test is used to determine the statistical significance of the trends in water quality over time (Gilbert 1987). It is a non-parametric test and is only used when the data series exhibits independence (i.e. no correlation in the data series) (Figure 2). The Mann-Kendall test works by calculating a statistic ‘S’ and testing the significance of this statistic. Each data pair is compared and assigned a plus or a minus depending on whether the later data point is higher than the earlier data point. ‘S’ is the overall number of pluses or minuses (where one plus cancels out one minus) for the whole dataset (Nelson 2004). The Z-statistic, from which the ‘p-value’ is derived, is calculated as follows:
Where Var(S) is the variance of the dataset used to derive ‘S’. An increasing trend will have a large positive Z-statistic, while the Z statistic for a decreasing trend will be negative and have a large absolute value.
Figure 2: Example of a time-series with little evidence of a seasonal pattern in total phosphorus concentration, hence the Mann-Kendall test for trend is used
Seasonal cycles in nutrient concentration are common in waterways and can be introduced by natural cycles in rainfall, runoff, tributary hydrology and seasonal variation in groundwater interaction. When seasonal cycles are evident in a data series (Figure 3), the Seasonal-Kendall test is used to test for trend. The Seasonal-Kendall test is a variant of the Mann-Kendall test that accounts for the presence of seasonal cycles in the data series (Gilbert 1987). The ‘S’ statistic is calculated slightly differently in the Seasonal-Kendall test. Rather than comparing all data pairs, only data points falling in the same ‘season’ are compared. For example, if a weekly season is used, data points from the first weeks of the year are only compared with data points from the first week of all other years.
Figure 3: An example of a pronounced seasonal pattern in total phosphorus concentration
Nutrient concentrations in waterways can also be affected by changes in flow. The relationship between nutrient concentration and flow is modelled using LOWESS fit between the concentration and flow (Helsel & Hirsch 1992). The difference of ‘residuals’ between the observed and LOWESS modelled concentration are termed flow-adjusted concentrations (FAC), as shown in Figure 5-9 (Hipel & McLeod 1994). Trend analyses may then be performed on the flow-adjusted concentrations. The flow-adjustment process often helps to remove seasonal variation (as shown by comparing Figures 3 and 4B), although some evidence of seasonal variation often remains in the flow-adjusted data series.
Figure 4: The flow response plot shows whether a relationship exists between discharge and nutrient concentration (A). The flow-adjusted concentrations (or residuals) are the difference between observed and modelled (LOWESS) concentrations (B).
3.2 Estimating the rate of change
The Sen slope estimator is used to estimate the slope of the trend line (Gilbert 1987). The Sen estimate is calculated in a similar manner to the test statistic ‘S’ from the Mann-Kendall test. Rather than comparing each data pair from an increase or decrease over time, a slope is calculated using each data pair. The Sen slope estimator is taken as the median slope of all slopes calculated using all data pairs. In the presence of seasonal cycles the Seasonal-Kendall slope estimator is used. This is similar to the seasonal test ‘S’ in the Seasonal-Kendall test, in that slopes are only calculated for data pairs from the same season. The Sen slope estimator is the median of all these slopes. Figure 5 shows an example of a slope estimated for a series showing seasonally.
Figure 5: An example of how the Seasonal Sen slope estimator represents the slope of the trend line in a seasonal nutrient data series.
Loads were calculated for those sites where there was sufficient flow and nutrient data available.
Annual loads were calculated by multiplying daily flow with daily nutrient concentration and aggregating over the year. Daily concentration measurements are not available as samples were taken weekly at most, so daily concentration data needs to be in-filled to calculate loads. To calculate the in-filled nutrient data the locally estimated scatterplot smoothing (LOESS) algorithm (Cleveland 1979) was used.
LOESS creates a flow-concentration curve by fitting a low-degree polynomial to a subset of the flow-concentration data to estimate the concentration for the flow at the centre point of the data subset. This is done for each flow value in the dataset. For days on which nutrient data were collected, daily loads are calculated from observed concentrations and flows. For days with no data, daily loads are calculated from the daily flow and the estimated concentration from the LOESS flow-concentration curve. The assumption of the LOESS algorithm is that there is a relationship between flow and concentration.
ANZECC & ARMCANZ, 2000, Australian and New Zealand guidelines for fresh and marine water quality, Australian and New Zealand Environment and Conservation Council & Agriculture and Resource Management Council of Australia and New Zealand.
Cleveland, WS 1979, Robust locally weighted regression and smoothing scatterplots, Journal of the American Statistical Association, Vol 74: 829-836.
Department of Water, 2014, WAter resources inventory 2014. Water availability, quality and trends, Department of Water, Western Australia.
Department of Water and Environmental Regulation, 2022, Bindjareb Djilba, a plan for the protection of the Peel-Harvey estuary, Department of Water and Environmental Regulation, Western Australia.
Gilbert, R 1987, Statistical methods for environmental pollution monitoring, Van Nostrand Reinhold, New York, 250 pp.
Hall, J 2010, Water quality management in urban catchments of the Swan Coastal Plain: analysis of the Bartram Road catchment, Water Science Technical Series, report no. 22, Department of Water, Western Australia.
Hipel, K & McLeod, A 1994, Time series modelling of environmental and water resources systems, Elsevier, Amsterdam.
Hugues-dit-Ciles, J, Kelsey, P, Marillier, B, Robb, M, Forbes, V & McKenna, M 2012, Leschenault estuary water quality improvement plan, Department of Water, Western Australia.
Nelson, S 2004, Planet (Version 5) user manual, Water and Rivers Commission, Perth, Western Australia.
SWRWQA 2009, Statewide river water quality assessment; accessed: 31/03/2022.
White, KS 2012, Hardy Inlet water quality improvement plan: Stage one – the Scott River catchment; Department of Water, Western Australia.
